gpt-gmm-polar-chart.py

# Get inclusion probabilities
probabilities = gmm.predict_proba(matrix)
proba_df = pd.DataFrame(probabilities, columns = aspect_labels.values())

# Get dominant aspects
fig = px.line_polar(
    pd.DataFrame({
        "aspect": proba_df.idxmax(axis=1),
        "max_proba": proba_df.lookup(proba_df.index, proba_df.idxmax(axis=1))
    }).groupby("aspect").sum().reset_index(), 
    r="max_proba", 
    theta="aspect", 
    line_close=True
)
fig.update_traces(fill='toself')
fig.update_layout(polar = dict(radialaxis = dict(showticklabels = False)))
fig.show()